public static final class
TensorShapeProto.Builder
Dimensions of a tensor.
tensorflow.TensorShapeProto
Public Methods
TensorShapeProto.Builder |
addAllDim(Iterable<? extends TensorShapeProto.Dim> values)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
addDim(TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
addDim(int index, TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
addDim(int index, TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
addDim(TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder |
addDimBuilder()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder |
addDimBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
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TensorShapeProto |
build()
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TensorShapeProto | |
TensorShapeProto.Builder |
clear()
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TensorShapeProto.Builder |
clearDim()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
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TensorShapeProto.Builder |
clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
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TensorShapeProto.Builder |
clearUnknownRank()
If true, the number of dimensions in the shape is unknown. |
TensorShapeProto.Builder |
clone()
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TensorShapeProto | |
final static com.google.protobuf.Descriptors.Descriptor | |
com.google.protobuf.Descriptors.Descriptor | |
TensorShapeProto.Dim |
getDim(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder |
getDimBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
List<TensorShapeProto.Dim.Builder> |
getDimBuilderList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
int |
getDimCount()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
List<TensorShapeProto.Dim> |
getDimList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.DimOrBuilder |
getDimOrBuilder(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
List<? extends TensorShapeProto.DimOrBuilder> |
getDimOrBuilderList()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
boolean |
getUnknownRank()
If true, the number of dimensions in the shape is unknown. |
final boolean | |
TensorShapeProto.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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TensorShapeProto.Builder |
mergeFrom(com.google.protobuf.Message other)
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final TensorShapeProto.Builder |
mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
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TensorShapeProto.Builder |
removeDim(int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
setDim(int index, TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
setDim(int index, TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Builder |
setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
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TensorShapeProto.Builder |
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
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final TensorShapeProto.Builder |
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
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TensorShapeProto.Builder |
setUnknownRank(boolean value)
If true, the number of dimensions in the shape is unknown. |
Inherited Methods
Public Methods
public TensorShapeProto.Builder addAllDim (Iterable<? extends TensorShapeProto.Dim> values)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder addDim (TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder addDim (int index, TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder addDim (int index, TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder addDim (TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Dim.Builder addDimBuilder ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Dim.Builder addDimBuilder (int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
public TensorShapeProto.Builder clearDim ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder clearUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
public TensorShapeProto.Dim getDim (int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Dim.Builder getDimBuilder (int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public List<TensorShapeProto.Dim.Builder> getDimBuilderList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public int getDimCount ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public List<TensorShapeProto.Dim> getDimList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.DimOrBuilder getDimOrBuilder (int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public List<? extends TensorShapeProto.DimOrBuilder> getDimOrBuilderList ()
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public boolean getUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
public final boolean isInitialized ()
public TensorShapeProto.Builder mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Throws
IOException |
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public final TensorShapeProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
public TensorShapeProto.Builder removeDim (int index)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder setDim (int index, TensorShapeProto.Dim value)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder setDim (int index, TensorShapeProto.Dim.Builder builderForValue)
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
repeated .tensorflow.TensorShapeProto.Dim dim = 2;
public TensorShapeProto.Builder setField (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
public TensorShapeProto.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
public final TensorShapeProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
public TensorShapeProto.Builder setUnknownRank (boolean value)
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;